根据在另一个表中找到的差异在一个表中插入、更新或删除行,可以对两个表进行同步。
A. 使用 MERGE 在单个语句中对表执行 UPDATE 和 DELETE 操作下面的示例使用 MERGE 根据 SalesOrderDetail 表中已处理的订单,每天更新 AdventureWorks 示例数据库中的 ProductInventory 表。通过减去每天对 SalesOrderDetail 表中的每种产品所下的订单数,更新 ProductInventory 表的 Quantity 列。如果某种产品的订单数导致该产品的库存量下降到 0 或更少,则会从 ProductInventory 表中删除该产品对应的行。
B. 借助派生的源表,使用 MERGE 对目标表执行 UPDATE 和 INSERT 操作
下面的示例使用 MERGE 以更新或插入行的方式来修改 SalesReason 表。当源表中的 NewName 值与目标表 (SalesReason) 的 Name 列中的值匹配时,就会更新此目标表中的 ReasonType 列。当 NewName 的值不匹配时,就会将源行插入到目标表中。此源表是一个派生表,它使用 Transact-SQL 行构造函数功能指定源表的多个行。有关在派生表中使用行构造函数的详细信息,请参阅 FROM (Transact-SQL)。
C. 将 MERGE 语句的执行结果插入到另一个表中
下例捕获从 MERGE 语句的 OUTPUT 子句返回的数据,并将该数据插入另一个表。MERGE 语句根据在 SalesOrderDetail 表中处理的订单,更新 ProductInventory 表的 Quantity 列。本示例捕获已更新的行,并将这些行插入用于跟踪库存变化的另一个表中
代码如下:
USE AdventureWorks;
GO
IF OBJECT_ID (N'Production.usp_UpdateInventory', N'P')
IS NOT NULL DROP PROCEDURE Production.usp_UpdateInventory;
GO
CREATE PROCEDURE Production.usp_UpdateInventory
@OrderDate datetime
AS
MERGE Production.ProductInventory AS target
USING (SELECT ProductID, SUM(OrderQty) FROM Sales.SalesOrderDetail AS sod
JOIN Sales.SalesOrderHeader AS soh
ON sod.SalesOrderID = soh.SalesOrderID
AND soh.OrderDate = @OrderDate
GROUP BY ProductID) AS source (ProductID, OrderQty)
ON (target.ProductID = source.ProductID)
WHEN MATCHED AND target.Quantity - source.OrderQty THEN DELETE
WHEN MATCHED
THEN UPDATE SET target.Quantity = target.Quantity - source.OrderQty,
target.ModifiedDate = GETDATE()
OUTPUT $action, Inserted.ProductID, Inserted.Quantity, Inserted.ModifiedDate, Deleted.ProductID,
Deleted.Quantity, Deleted.ModifiedDate;
GO
EXECUTE Production.usp_UpdateInventory '20030501'
代码如下:
USE AdventureWorks;
GO
MERGE INTO Sales.SalesReason AS Target
USING (VALUES ('Recommendation','Other'), ('Review', 'Marketing'), ('Internet', 'Promotion'))
AS Source (NewName, NewReasonType)
ON Target.Name = Source.NewName
WHEN MATCHED THEN
UPDATE SET ReasonType = Source.NewReasonType
WHEN NOT MATCHED BY TARGET THEN
INSERT (Name, ReasonType) VALUES (NewName, NewReasonType)
OUTPUT $action, inserted.*, deleted.*;
代码如下:
USE AdventureWorks;
GO
MERGE INTO Sales.SalesReason AS Target
USING (VALUES ('Recommendation','Other'), ('Review', 'Marketing'), ('Internet', 'Promotion'))
AS Source (NewName, NewReasonType)
ON Target.Name = Source.NewName
WHEN MATCHED THEN
UPDATE SET ReasonType = Source.NewReasonType
WHEN NOT MATCHED BY TARGET THEN
INSERT (Name, ReasonType) VALUES (NewName, NewReasonType)
OUTPUT $action, inserted.*, deleted.*;
代码如下:
USE AdventureWorks;
GO
CREATE TABLE Production.UpdatedInventory
(ProductID INT NOT NULL, LocationID int, NewQty int, PreviousQty int,
CONSTRAINT PK_Inventory PRIMARY KEY CLUSTERED (ProductID, LocationID));
GO
INSERT INTO Production.UpdatedInventory
SELECT ProductID, LocationID, NewQty, PreviousQty
FROM
( MERGE Production.ProductInventory AS pi
USING (SELECT ProductID, SUM(OrderQty)
FROM Sales.SalesOrderDetail AS sod
JOIN Sales.SalesOrderHeader AS soh
ON sod.SalesOrderID = soh.SalesOrderID
AND soh.OrderDate BETWEEN '20030701' AND '20030731'
GROUP BY ProductID) AS src (ProductID, OrderQty)
ON pi.ProductID = src.ProductID
WHEN MATCHED AND pi.Quantity - src.OrderQty >= 0
THEN UPDATE SET pi.Quantity = pi.Quantity - src.OrderQty
WHEN MATCHED AND pi.Quantity - src.OrderQty THEN DELETE
OUTPUT $action, Inserted.ProductID, Inserted.LocationID, Inserted.Quantity AS NewQty, Deleted.Quantity AS PreviousQty)
AS Changes (Action, ProductID, LocationID, NewQty, PreviousQty) WHERE Action = 'UPDATE';
GO

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

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MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.

MySQL asynchronous master-slave replication enables data synchronization through binlog, improving read performance and high availability. 1) The master server record changes to binlog; 2) The slave server reads binlog through I/O threads; 3) The server SQL thread applies binlog to synchronize data.

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

The installation and basic operations of MySQL include: 1. Download and install MySQL, set the root user password; 2. Use SQL commands to create databases and tables, such as CREATEDATABASE and CREATETABLE; 3. Execute CRUD operations, use INSERT, SELECT, UPDATE, DELETE commands; 4. Create indexes and stored procedures to optimize performance and implement complex logic. With these steps, you can build and manage MySQL databases from scratch.

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MySQL is suitable for beginners because it is simple to install, powerful and easy to manage data. 1. Simple installation and configuration, suitable for a variety of operating systems. 2. Support basic operations such as creating databases and tables, inserting, querying, updating and deleting data. 3. Provide advanced functions such as JOIN operations and subqueries. 4. Performance can be improved through indexing, query optimization and table partitioning. 5. Support backup, recovery and security measures to ensure data security and consistency.


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